CloudEagle.ai

Your marketing manager has admin access to AWS. Nobody remembers granting it. It happened during a migration two years ago, carried over through two role changes, and survived three quarterly access reviews because the manager who rubber-stamped it assumed someone else had checked. This is privilege creep. And it is not rare. Our IGA Report found that 1 in 2 employees currently has more access than their role requires. The average time before it gets flagged is 89 days. EagleEye does not wait for the quarterly review. It monitors access continuously, scores risk in real time using AI, and flags excessive privileges the moment they appear. When your marketing manager gets AWS admin access that they should not have, EagleEye catches it that day. Not at the next review cycle. Every approval is tracked. Every deprovisioning is logged. When your auditor asks for evidence, it is already there. Because a 89-day exposure window is not a review problem. It is a monitoring problem. And a quarterly spreadsheet cannot fix it. Read more about EagleEye in action, link in comments.

When someone leaves your organisation, deprovisioning their Microsoft 365 account used to mean revoking their license. Their Security Groups and Microsoft 365 Groups stayed intact until someone manually cleaned them up in Azure, which often never happened. CloudEagle.ai now lets you configure group removal as part of the Microsoft 365 deprovisioning workflow. When setting up deprovisioning actions, you select which Security Groups and Microsoft 365 Groups the user should be removed from. When the workflow runs, group removal happens automatically alongside license revocation, and every action is logged in the workflow activity trail. No separate Azure admin tasks or groups left behind. Full deprovisioning in one workflow. Available now for teams using Microsoft 365 in CloudEagle.

If you are in Chicago on April 22 and work in IT, security, finance, or procurement, this one is for you. We are hosting Dine & Dash at Kindling with HCL BigFix. Drop in anytime between 4:30 and 6:30 PM. There's no boring agenda, presentations, or awkwardly structured networking. Just a curated group of professionals, a good venue, and dinner handled. The conversations that actually move things forward rarely happen in conference rooms. They happen when the agenda is gone, and people can just talk. Limited spots. RSVP link in comments.

Your organisation has a policy for which AI tools employees can use. It does not have a policy for what happens when those AI tools start acting autonomously on behalf of your employees. AI agents are different from AI assistants. An assistant answers a question. An agent takes an action, it sends an email, updates a record, provisions a resource, and connects to an API. And it does all of this using credentials that were granted to it at setup and never reviewed again. This is the identity governance problem nobody has written a policy for yet. When a human employee gets excessive access, your access review catches it eventually. When an AI agent gets excessive access, it does not show up in any review because it is not a human identity. It does not have an employee record. It does not appear in your IdP. And it is making decisions and taking actions in your environment around the clock. The question to ask your security team this week is simple. How many AI agents are currently operating in your environment, what credentials do they have, and who is responsible for reviewing their access? If the answer to any of those is "we are not sure," you have a gap that no current governance framework is covering. Non-human identity governance is not a 2027 problem. It is already running in your stack.

When 60% of your software stack bypasses IT, the problem is not your employees. The problem is that your approved process is slower than the problem employees are trying to solve. So they find a tool, sign up, and get to work. By the time IT finds out, the tool is embedded in three team workflows, has OAuth access to two core systems, and removing it would cost more in lost productivity than the security risk it represents. This is the reality of enterprise software adoption in 2026. And a governance framework that treats this as a compliance failure will keep losing to it. The op-ed makes the case for why the answer is not stricter controls but faster, more visible governance: a model where IT can see everything that is running, score it by risk, and act on the ones that actually matter rather than trying to stop adoption entirely. Full piece in the comments.

Your access review looked clean. It always does on paper. What it doesn't show is the 60% of access that never made it into the review: the apps that bypass SSO, the OAuth connections nobody mapped, the contractor whose project ended five months ago but whose account is still active. This is how access risk accumulates quietly in every enterprise running manual reviews. Swipe to see exactly how it happens 👉How long did your last access review take from start to finish?

New Feature Alert 🚨 CloudEagle.ai now gives enterprises GenAI risk scores for every vendor in their SaaS stack. Boards are forming AI risk committees and asking for documented proof that vendor AI practices are understood and governed. 70% of CIOs flag unsanctioned AI tools as their top data concern, yet most enterprises have no way to assess what risk those vendors actually carry. Which tools train AI on customer data? Which AI features can be disabled? Which vendors meet SOC 2 or ISO 27001 standards? These questions used to require manual research across hundreds of vendor documentation pages. CloudEagle.ai now answers them automatically, across every vendor in the portfolio. Here's what's now visible for every application in your stack: 🔴 AI Training Exposure: Whether the vendor uses your data to train AI models  🔴 AI Disable Controls: Whether AI features can be turned off at the enterprise level ✅ MFA Support: Whether multi-factor authentication is enforced  ✅ Certifications: SOC 2, ISO 27001, and other compliance standards  ✅ SSO Support: Whether the app integrates with your identity providers  ✅ Data Center Standards: Infrastructure and data residency requirements All of it is searchable and filterable across your full SaaS portfolio. All of it sits inside each vendor's profile, next to spend, usage, and contract data. Massive thanks to the CloudEagle team for building this. When boards are asking for documented proof, your security team should be able to answer in seconds. Press release link in comments. 🚀